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European Agentic AI Bootcamp

openhackathonsHosted on Open Hackathons

Fetched about 8 hours ago

Monday, July 20, 2026

to Wednesday, July 22, 2026

•

2 days long

Artificial IntelligenceMachine LearningInnovationNetworkingCommunity

Event Type

online

This Bootcamp is co-organized by Austrian Scientific Computing (ASC), the Leibniz Supercomputing Centre (LRZ), the High-Performance Computing Center Stuttgart (HLRS), the Academic Computer Centre Cyfronet AGH (Cyfronet), OpenACC organization, and NVIDIA for AI Factory Austria AI:AT, HammerHAI, and Gaia AI Factory and will host a virtual European Agentic AI Bootcamp starting 20 July, 2026 and concluding 22 July, 2026. Agentic AI employs sophisticated reasoning to solve complex problems, utilizing data from multiple sources to analyze, strategize, and complete tasks independently. There are many powerful building blocks that developers and researchers can use to enable and accelerate the development and deployment of their agentic AI workflows.The European Agentic AI Bootcamp covers some of these powerful tools, including Agent Skills, which are folders of instructions, scripts, and resources that agents can discover to grant them domain expertise and new capabilities; Model Context Prot

Judge Accessibility

Organizer email available25/25
Student-run event15/15
Actively looking for judges25/25
Small event (120 participants)10/10
No corporate sponsors10/10
New or emerging organizer10/10
Public registration available5/5
Online format (judge from anywhere)10/10

Top signals

Organizer email available
Student-run event
Actively looking for judges

Organizers

Alex Johnson

alex@example.org

Jamie Rivera

jamie@example.org

Sam Chen

sam@example.org

Estimated Audience

Mostly Students
ExperienceStudent
OccupationStudents
Beginner Friendly
Women in Tech

Technical Focus

AI95%
Web80%
Mobile25%

Industries

Healthcare
Education
Climate

Technologies

Python
React
OpenAI

Why this estimate

  • • Hosted by a university
  • • Open to students
  • • MLH member event

Estimate inferred from event metadata, not actual attendee data.

Quality Score

Quality Score

72/100
High confidence
Organiser16/20
Event Maturity14/20
Sponsors18/25
Participants12/20
Operations12/15

Why this score

Strong organiser track record
Returning event
Well-sponsored

Missing data

Prize details
Code of conduct